reactive maintenance, also known as run to failure
reactive maintenance, also known as run to failure

Mean Time Between Failures

The technology of today never stops, or so it may seem. A simple equation that predicts when downtime or critical equipment failure could happen can limit serious repercussions.

What is mean time between failures (MTBF)?

Mean time between failures (MTBF) is the average time between a failure or breakdown of critical technological systems or mechanics during regular operations. Created by the aviation industry as a safety and reliability metric, other industries discovered the benefit of knowing when downtime might occur and adopted MTBF.

Measured in hours, the MTBF value focuses on unplanned maintenance and keeps preventive maintenance and inspections out of its equation. It can help operators define asset life expectancy, potential uptime, and equipment reliability.

Often, MTBF is used to create preventive maintenance schedules for equipment and assets to ensure service is performed before a likely breakdown.

The objective of MTBF is to allow organizations to operate for as many hours as possible. The more time between failures, the more work that can be accomplished. MTBF delivers a considerable reassurance that operations can go on as planned without the need for repair.

How do you calculate mean time between failures?

MTBF is a simple calculation that divides the total number of operational hours in a given period by the number of failures that occurred during that same time. Its solution reveals the hours of runtime before technology or equipment breaks down. The equation is:

MTBF = number of operational hours divided by number of failures

For example, after running 2,000 hours, let’s say a ceramic manufacturer’s kiln created impurities in the ware 10 times and had to be shut down. Using the formula above, the kiln has an MTBF of 200 hours.

Some equipment manufacturers will provide an MTBF estimate in their machine’s manuals, but it’s highly discouraged to use that number. Actual performance hours and breakdown maintenance numbers are the only way to measure an organization’s assets reliably.

What does an asset's mean time between failures value determine?

MTBF can give you an educated prediction of the chances that a piece of machinery will fail. In our example above, it’s an easy jump to hypothesize that after 200 hours, our ceramic manufacturer will have to shut down the kiln again. This can help inform a maintenance plan and maintenance tasks in the following ways:

  • Defining a preventive maintenance schedule: Knowing an asset’s MTBF can better outline when preventive maintenance tasks should be performed, and parts ordered. It can prevent failures, breakdowns, and emergency repairs.
  • Preparing for downtime: MTBF can prepare a plant or organization for predicted downtime. Work can shift to another area, and maintenance repair time can be shortened as everyone knows an asset may go down.
  • Making capital expenditure decisions: If an asset’s MTBF continues to fall, it may be time to replace the asset. MTBF can become solid proof of catastrophic failure that can save on longterm repair and maintenance costs.

To gain an even bigger picture of an asset’s functionality, MTBF can be used in conjunction with root cause analysis, failure codes, and metrics like mean time to repair (MTTR) and mean time to failure (MTTF). We’ll take a look at MTTR and MTTF in just a moment.

MTTR is the time between failure and repair. MTBF is the time between repair and next failure.

How to improve MTBF

Bad data in, bad data out. The first thing a technician in an organization has to do to improve MTBF values is to ensure that the data they collect is accurate. Otherwise, maintenance teams can become locked into a never-ending, costly breakdown maintenance cycle.

There are several ways to collect MTBF data, but the leading recording tools are CMMS software. A CMMS can easily track breakdowns, repairs, parts, and downtime. Historical records of work and maintenance needs of any machine or piece of equipment are available at an organization’s fingertips.

The next thing that can help improve MTBF is implementing a preventive maintenance schedule. A preventive maintenance strategy can prolong the life of machinery and lengthen the time between breakdowns and emergency repair significantly. Everything from oil changes to inspections can be planned repairs for a savvy maintenance operation.

Another way to improve MTBF is to frequently track MTBF metrics. There will be no surprises for a production crew or maintenance team by always being engaged.

More metrics—what is the difference between MTBF, MTTF, and MTTR?

There are more metrics that can help organizations predict breakdowns and failures.

Mean time to failure (MTTF)

Along with MTBF, there is mean time to failure (MTTF). Like MTBF, MTTF measures time, but it measures how much life equipment has before it completely breaks down or has maintenance issues.

Also known as asset lifespan, the equation is similar to MTBF but is only used for non-repairable assets, like forklift wheels, transistors, and fan belts:

MTTF equals total operating time divided by total assets in use

This is another way to gauge when new assets may need to be purchased.

Mean time to repair (MTTR)

Mean time to recovery or mean time to repair (MTTR) is another useful metric. MTTR is the average time to fully repair a system or asset. Its equation is:

mean time to repair (MTTR) equals total repair time divided by number of repairs


Organizations can use MTBF and MTTR to generate availability metrics: the duration of time a specific piece of equipment can perform the task for which it was designed. It’s a way of determining the actual time a machine has operated. The equation is:

Availability = MTBF divided by the sum of MTBF and MTTR

In a manufacturing environment, this value can help in improving production quota speed and MTBF by effectively demonstrating equipment uptime.

Which metric should an organization use? How about all of them? Each tells their own story about the health and efficiency of maintenance teams and assets—and where improvements can be made.

A comparison chart of common incident metrics. Mean time between failures (MTBF) measures the average time between a failure or breakdown of a repairable asset. Mean time to failure measures how much life a non-repairable asset has before it completely breaks down. Mean time to repair measures the average time to fully repair a system or asset. Availability is the duration of time a specific repairable asset can perform the task for which it was designed.


Tracking mean time between failures is essential in improving unplanned repairs and downtime in a facility. Knowing MTBF can help advance reliability and asset life. Predicting failures can lead to shorter repair times and having an organization prepared and ready for any maintenance work.

Coupling MTBF with maintenance management software and preventive maintenance schedules creates a robust maintenance method and strategy that can save time and money for any industry.